Evaluation of tree growth characteristics of harum manis mango from multitemporal UAV image in plantation farm

Innovations in Unmanned Aerial Vehicle (UAV) technology and data processing capacities have made it easier to collect high-resolution images and 3D data that can be used to monitor and measure tree characteristics in agriculture. This research explores the performance of high spatial resolution UAV imagery to estimate tree height and crown dimensions for Mango Tree. Furthermore, high-resolution spatial imagery generated by unmanned aerial vehicles (UAVs) can provide precise and effective estimate of tree measurements and structural canopy variables. The aim of this study is monitor Harum Manis tree growth and crown canopy diameter using multitemporal UAV image in plantation farm. This research will use Agisoft PhotoScan to process multitemporal data and eCognition for analyse object-based image analysis (OBIA). The study area for this research is in University Teknologi Mara Arau Perlis at Harum Manis mango farm. The contribution of this study is to produce Canopy Height Mapping (CHM) from difference multitemporal UAV data and characterization of mango tree develop using OBIA algorithm to monitoring development Harum Manis Tree. The RMSE for May 2019 is 0.315m with R2=0. 8115.Combination OBIA and UAV can be used for monitoring crop.